The AI promise was automation. The reality? Managing digital workers
When artificial intelligence agents first arrived, they came with a tantalising promise: autonomous “digital workers” that would finally free humans from corporate drudgery. As businesses across Asia are discovering, however, the reality is quite the opposite – more work, new friction and a whole new layer of management. When Xiao Mengjie, an AI product marketing manager at a Big Tech firm in…
When artificial intelligence agents first emerged, they promised to automate mundane corporate tasks, freeing humans from tedious work. However, businesses in Asia are discovering that the reality is quite different – AI agents are creating more work, new friction, and requiring additional management layers. Xiao Mengjie, an AI product marketing manager in Shanghai, assigned two AI agents to a simple task, expecting efficiency.
Instead, she encountered corporate gridlock, as her agent and her supervisor's agent argued over responsibilities, creating a bureaucratic situation similar to the one they were meant to replace. This communication overhead is a common issue across Asia, where businesses have embraced the idea of autonomous software capable of handling complex workflows with minimal human intervention.
Meta's personal agent Muse and OpenClaw, a Chinese open-source agent, have seen massive adoption, but many businesses are facing challenges in managing these digital workers effectively. Deploying AI agents in complex environments, such as hotel operations or travel industry workflows, often proves more difficult than anticipated.
The agents struggle to navigate fragmented systems, determine when human intervention is necessary, and coordinate across multiple departments. Additionally, legacy technology systems and organizational resistance in countries like Hong Kong slow down AI adoption, particularly in sectors like banking and insurance where data security concerns are paramount.
Despite these hurdles, the demand for AI agents continues to grow, but organizations must address the underlying governance challenges to ensure these autonomous systems remain accountable and aligned with human objectives.
Written by urgent.news from SCMP Tech's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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